NOW PAID MEDIA WILL STEP INTO THE LIGHT TO BECOME A TRUSTED REVENUE-DRIVER, WITH YOU FIRMLY IN THE DRIVER’S SEAT.

Meet “HamiltonAI”

Blackwood Seven is a Media AI Platform helping Marketing optimize future media investments and predict the business results. The platform applies artificial intelligence and machine learning to media planning across all offline and online media channels – and it is powered by HamiltonAI.

Hamilton AI is the first in-silico data scientist in the world and it is trained to measure the effect of past media investments and run a multitude of investment scenarios to optimize future media plans and predict the effect.

In this video, we will explain what HamiltonAI is and why what is does is different from traditional Marketing Mix Modelling.

HamiltonAI is based on Bayesian Probabilistic Hierarchical Networks. It utilises a Domain Specific Language to create a general-purpose network between variables, parameters and data.

It relies on principles of Bayesian statistics – which always has prior assumptions before observing data. HamiltonAI excels at making connections between real life constraints and observed data and therefore builds models in the same way that a human would. Only better.

HamiltonAI is able to model the synergistic effects for all individual off- and online publishers over time – providing granularity and liberating the model from considering the variables as independent. It even allows for a hierarchy of the variables and the ability to sub-categorise them.

So for example, if you had 100 display banners running at the same time, HamiltonAI can measure the effect of all of them individually. This allows for very elaborate and granular model outputs.

Measuring every ”node” in the network of advertising variables requires complex modelling and a lot of computing power – the result is that we understand how every piece of paid media affects the other over time. This granularity allows us to decompose data for any given time and dive-deep into how specific TV spots and display banners impact the objective.

Since we can typically relate the model objective to profit and we now have a granular way of attributing paid media to the objective, we solidify a previously tentative link. We can now accurately calculate our short to medium term return on all paid media investments.

HamiltonAI also include macroeconomics and other external factors that can impact the effect of paid media.

All marketing actions and performance metrics are obviously included, but also data to describe the market conditions such as consumer confidence, unemployment rates and competitive activity including paid media investments and changes to product and pricing.

Additionally, to this level of intricacy and granularity, HamiltonAI is also exceedingly flexible. We can brief Hamilton AI on the knowledge we have about a market which enables it to reason together with a human. By providing HamiltonAI with the constraints and subtleties about individual markets, we can take the best of the computational power of data and inferential reasoning to create accurate predictions on future media investment scenarios and quantify the objective as well as the profit the different scenarios will generate.

A fundamental difference between HamiltonAI and other AI approaches that automate the model creation is that Hamilton poses a scientific question versus purely hypothesis generation by maximising likelihood of observing a data set.

Just as in the world of finance, risk plays a big role in decisions to invest in paid media and HamiltonAI enables us to make informed decisions based on our risk averseness

Finally, the world is not static. The efficiency of marketing and media changes constantly and Hamilton AI has therefore been built for continuous learning. A data consolidation layer collects and ingests new data when available and HamiltonAI updates the model and makes the results available. A slow and labour intensive process with traditional marketing mix models, made fast and easy with Blackwood Seven and HamiltonAI.